U.S. patent application number 15/851176 was filed with the patent office on 2018-08-02 for system and method for monitoring respiratory rate measurements.
The applicant listed for this patent is MASIMO CORPORATION. Invention is credited to Ammar Al-Ali, Bilal Muhsin, Michael O'Reilly.
Application Number | 20180214090 15/851176 |
Document ID | / |
Family ID | 48146035 |
Filed Date | 2018-08-02 |
United States Patent
Application |
20180214090 |
Kind Code |
A1 |
Al-Ali; Ammar ; et
al. |
August 2, 2018 |
SYSTEM AND METHOD FOR MONITORING RESPIRATORY RATE MEASUREMENTS
Abstract
This disclosure describes, among other features, systems and
methods for using multiple physiological parameter inputs to
determine multiparameter confidence in respiratory rate
measurements. For example, a patient monitoring system can
programmatically determine multiparameter confidence in respiratory
rate measurements obtained from an acoustic sensor based at least
partly on inputs obtained from other non-acoustic sensors or
monitors. The patient monitoring system can output a multiparameter
confidence indication reflective of the programmatically-determined
multiparameter confidence. The multiparameter confidence indication
can assist a clinician in determining whether or how to treat a
patient based on the patient's respiratory rate.
Inventors: |
Al-Ali; Ammar; (San Juan
Capistrano, CA) ; Muhsin; Bilal; (San Clemente,
CA) ; O'Reilly; Michael; (San Jose, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
MASIMO CORPORATION |
Irvine |
CA |
US |
|
|
Family ID: |
48146035 |
Appl. No.: |
15/851176 |
Filed: |
December 21, 2017 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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14752466 |
Jun 26, 2015 |
9877686 |
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15851176 |
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12905449 |
Oct 15, 2010 |
9066680 |
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14752466 |
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61252086 |
Oct 15, 2009 |
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61261199 |
Nov 13, 2009 |
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61366866 |
Jul 22, 2010 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
A61B 5/0803 20130101;
A61B 5/0816 20130101; G16H 40/67 20180101; A61B 5/14542 20130101;
A61B 5/021 20130101; G16H 40/63 20180101; A61B 5/02416 20130101;
A61B 5/044 20130101; A61B 5/024 20130101; A61B 5/0205 20130101;
A61B 5/746 20130101; A61B 5/7221 20130101; A61B 5/742 20130101;
A61B 5/14551 20130101; A61B 7/003 20130101; A61B 5/7278 20130101;
A61B 5/0402 20130101; G16H 40/60 20180101; G06F 19/3418
20130101 |
International
Class: |
A61B 5/00 20060101
A61B005/00; A61B 5/0205 20060101 A61B005/0205; A61B 5/024 20060101
A61B005/024; A61B 5/0402 20060101 A61B005/0402; A61B 5/08 20060101
A61B005/08; A61B 5/1455 20060101 A61B005/1455; A61B 7/00 20060101
A61B007/00 |
Claims
1-20. (canceled)
21. A system for monitoring a respiratory rate measurement from a
patient, the system comprising: one or more hardware processors
configured to: receive an acoustic signal generated by an acoustic
sensor responsive to vibrations of a patient, determine, from the
acoustic signal, a first measurement of a respiratory rate,
determine a first range of measurements of the respiratory rate
from one or more characteristics of the patient, the first range of
measurements forming a first safety zone, and determine a second
range of measurements of the respiratory rate from the one or more
characteristics, the second range of measurements forming a second
safety zone, the second range of measurements being different from
the first range of measurements and representing a greater safety
risk to the patient than the first range of measurements; and a
display configured to present the first safety zone and the second
safety zone together with an indicator, the indicator being
positioned according to the first measurement, a position of the
indictor relative to the first safety zone and the second safety
zone denoting whether the first measurement is within the first
range of measurements or the second range of measurements and
denoting a degree of safety concern for the patient estimated from
the first measurement.
22. The system of claim 21, wherein when at least one of the one or
more characteristics has a first magnitude, the display is
configured to present the indicator so that the position of the
indicator denotes that the first measurement is within the first
range of measurements and denotes that the degree of safety concern
is less than if the first measurement were within the second range
of measurements, and when at least one of the one or more
characteristics has a second magnitude different from the first
magnitude, the display is configured to present the indicator so
that the position of the indicator denotes that the first
measurement is within the second range of measurements and denotes
that the degree of safety concern is greater than if the first
measurement were within the first range of measurements.
23. The system of claim 21, wherein when at least one of the one or
more characteristics is within a first category, the display is
configured to present the indicator so that the position of the
indicator denotes that the first measurement is within the first
range of measurements and denotes that the degree of safety concern
is less than if the first measurement were within the second range
of measurements, and when at least one of the one or more
characteristics is within a second category different from the
first category, the display is configured to present the indicator
so that the position of the indicator denotes that the first
measurement is within the second range of measurements and denotes
that the degree of safety concern is greater than if the first
measurement were within the first range of measurements.
24. The system of claim 21, wherein the one or more characteristics
comprises a comorbidity for the patient.
25. The system of claim 21, wherein the one or more characteristics
comprises a medication being used by the patient.
26. The system of claim 21, wherein the one or more characteristics
comprises an age of the patient.
27. The system of claim 21, wherein the one or more characteristics
comprises a gender of the patient.
28. The system of claim 21, wherein the one or more characteristics
comprises an activity engaged in by the patient.
29. The system of claim 21, wherein the one or more hardware
processors is configured to determine a third range of measurements
of the respiratory rate from the one or more characteristics, the
third range of measurements forming a third safety zone, the third
range of measurements being different from the first range of
measurements and the second range of measurements, the third range
of measurements representing a greater safety risk to the patient
than the second range of measurements; and the display is
configured to present the first safety zone, the second safety
zone, and the third safety zone together with the indicator, the
position of the indictor relative to the first safety zone, the
second safety zone, and the third safety zone denoting whether the
first measurement is within the first range of measurements, the
second range of measurements, or the third range of measurements
and denoting the degree of safety concern for the patient estimated
from the first measurement.
30. The system of claim 21, wherein the one or more hardware
processors is configured to determine, from the acoustic signal, a
second measurement of the respiratory rate, the second measurement
being different from the first measurement; and the display is
configured to reposition the indicator according to the second
measurement so that the position of the indicator relative to the
first safety zone and the second safety zone denotes whether the
second measurement is within the first range of measurements or the
second range of measurements and denotes the degree of safety
concern for the patient estimated from the second measurement.
31. The system of claim 21, wherein the one or more hardware
processors is configured to activate an alarm responsive to the
first measurement being within the first range of measurements.
32. The system of claim 21, wherein the one or more hardware
processors is configured to change the one or more characteristics
responsive to a user input.
33. The system of claim 21, wherein the display is configured to
present the first safety zone in a first color and the second
safety zone in a second color different from the first color.
34. The system of claim 21, wherein the display is configured to
present a numerical value of the first measurement together with
the first safety zone, the second safety zone, and the
indicator.
35. A method for monitoring a respiratory rate measurement from a
patient, the method comprising: receiving, by one or more hardware
processors, an acoustic signal generated by an acoustic sensor
responsive to vibrations of a patient; determining, by the one or
more hardware processors from the acoustic signal, a first
measurement of a respiratory rate; determining, by the one or more
hardware processors, a first range of measurements of the
respiratory rate from one or more characteristics of the patient,
the first range of measurements forming a first safety zone;
determining, by the one or more hardware processors, a second range
of measurements of the respiratory rate from the one or more
characteristics, the second range of measurements forming a second
safety zone, the second range of measurements being different from
the first range of measurements and representing a greater safety
risk to the patient than the first range of measurements; and
presenting, by a display, the first safety zone and the second
safety zone together with an indicator, the indicator being
positioned according to the first measurement, a position of the
indictor relative to the first safety zone and the second safety
zone denoting whether the first measurement is within the first
range of measurements or the second range of measurements and
denoting a degree of safety concern for the patient estimated from
the first measurement.
36. The method of claim 35, wherein said presenting comprises
presenting the indicator so that the position of the indicator
denotes that the first measurement is within the first range of
measurements and denotes that the degree of safety concern is less
than if the first measurement were within the second range of
measurements, and further comprising: changing the one or more
characteristics to obtain a changed one or more characteristics;
determining, by the one or more hardware processors from the
acoustic signal, a second measurement of the respiratory rate, the
second measurement being the same as the first measurement;
adjusting, by the one or more hardware processors, the first range
of measurements according to the changed one or more
characteristics to obtain an adjusted first range of measurements
that forms an adjusted first safety zone; adjusting, by the one or
more hardware processors, the second range of measurements
according to the changed one or more characteristics to obtain an
adjusted second range of measurements that forms an adjusted second
safety zone; and presenting, by the display, the adjusted first
safety zone and the adjusted second safety zone together with the
indicator positioned according to the second measurement so that
the position of the indictor relative to the adjusted first safety
zone and the adjusted second safety zone denotes that the second
measurement is within the adjusted second range of measurements and
denotes that the degree of safety concern is greater than if the
second measurement were within the adjusted first range of
measurements.
37. The method of claim 35, wherein the one or more characteristics
comprises two or more of: a comorbidity for the patient, a
medication being used by the patient, an age of the patient, a
gender of the patient, or an activity engaged in by the
patient.
38. The method of claim 35, further comprising determining, by the
one or more hardware processors, a third range of measurements of
the respiratory rate from the one or more characteristics, the
third range of measurements forming a third safety zone, the third
range of measurements being different from the first range of
measurements and the second range of measurements, the third range
of measurements representing a greater safety risk to the patient
than the second range of measurements, wherein said presenting
comprises presenting, by the display, the first safety zone, the
second safety zone, and the third safety zone together with the
indicator, the position of the indictor relative to the first
safety zone, the second safety zone, and the third safety zone
denoting whether the first measurement is within the first range of
measurements, the second range of measurements, or the third range
of measurements and denoting the degree of safety concern for the
patient estimated from the first measurement.
39. The method of claim 35, further comprising activating, by the
one or more hardware processors, an alarm in response to the first
measurement being within the first range of measurements.
40. The method of claim 35, further comprising changing, by the one
or more hardware processors, the one or more characteristics in
response to a user input.
Description
RELATED APPLICATIONS
[0001] This application is a continuation of U.S. patent
application Ser. No. 14/752,466, filed Jun. 26, 2015, entitled
"SYSTEM FOR DETERMINING CONFIDENCE IN RESPIRATORY RATE
MEASUREMENTS," which is a continuation of U.S. patent application
Ser. No. 12/905,449, filed Oct. 15, 2010, entitled "SYSTEM FOR
DETERMINING CONFIDENCE IN RESPIRATORY RATE MEASUREMENTS," which
claims priority from U.S. Provisional Patent Application No.
61/252,086 filed Oct. 15, 2009, entitled "Pulse Oximetry System for
Determining Confidence in Respiratory Rate Measurements," from U.S.
Provisional Patent Application No. 61/261,199, filed Nov. 13, 2009,
entitled "Pulse Oximetry System with Adjustable Alarm Delay," and
from U.S. Provisional Patent Application No. 61/366,866, filed Jul.
22, 2010, entitled "Pulse Oximetry System for Determining
Confidence in Respiratory Rate Measurements," the disclosures of
which are hereby incorporated by reference in their entirety.
BACKGROUND
[0002] Hospitals, nursing homes, and other patient care facilities
typically include patient monitoring devices at one or more
bedsides in the facility. Patient monitoring devices generally
include sensors, processing equipment, and displays for obtaining
and analyzing a patient's physiological parameters. Physiological
parameters include, for example, blood pressure, respiratory rate,
oxygen saturation (SpO.sub.2) level, other blood constitutions and
combinations of constitutions, and pulse, among others. Clinicians,
including doctors, nurses, and certain other caregiver personnel
use the physiological parameters obtained from the patient to
diagnose illnesses and to prescribe treatments. Clinicians can also
use the physiological parameters to monitor a patient during
various clinical situations to determine whether to increase the
level of care given to the patient. Various patient monitoring
devices are commercially available from Masimo Corporation
("Masimo") of Irvine, Calif.
[0003] During and after surgery and in other care situations,
respiratory rate is a frequently monitored physiological parameter
of a patient. Respiratory rate can be indicated as the number of
breaths a person takes within a certain amount of time, such as
breaths per minute. For example, a clinician (such as a nurse,
doctor, or the like) can use respiratory rate measurements to
determine whether a patient is experiencing respiratory distress
and/or dysfunction.
SUMMARY OF DISCLOSURE
[0004] A system for determining multiparameter confidence in a
respiratory rate measurement from a medical patient, the system
comprising: an optical sensor comprising: a light emitter
configured to impinge light on body tissue of a living patient, the
body tissue comprising pulsating blood, and a detector responsive
to the light after attenuation by the body tissue, wherein the
detector is configured to generate a photoplethysmographic signal
indicative of a physiological characteristic of the living patient;
an ECG sensor configured to obtain an electrical signal from the
living patient; an acoustic sensor, the acoustic sensor configured
to obtain an acoustic respiratory signal from the living patient;
and a processor configured to: derive a first respiratory rate
measurement from the acoustic respiratory signal, derive a second
respiratory rate measurement from one or both of the
photoplethysmographic signal and the electrical signal, and use the
second respiratory rate measurement to calculate a confidence in
the first respiratory rate measurement.
[0005] A system for determining confidence in a respiratory rate
measurement from a medical patient, the system comprising: a first
physiological sensor configured to obtain a physiological signal
from a patient, the first physiological sensor comprising at least
one of the following: an ECG sensor, a bioimpedance sensor, and a
capnography sensor; an acoustic sensor configured to obtain an
acoustic respiratory signal from the living patient; and a
processor configured to: obtain a first respiratory rate
measurement from the physiological signal, obtain a second
respiratory rate measurement from the acoustic respiratory signal,
and calculate a confidence in the first respiratory rate
measurement responsive to the first and second respiratory rate
measurements.
[0006] A method of analyzing respiratory rate monitoring parameters
to determine confidence in a measured respiratory rate, the method
comprising: obtaining a first respiratory measurement from a first
physiological device, the first physiological device comprising an
acoustic sensor; obtaining a second respiratory measurement from a
second physiological device; determining a third respiratory rate
measurement based at least in part on the first and second
respiratory rate measurements; and outputting the third respiratory
rate measurement.
[0007] For purposes of summarizing the disclosure, certain aspects,
advantages and novel features of the inventions have been described
herein. It is to be understood that not necessarily all such
advantages can be achieved in accordance with any particular
embodiment of the inventions disclosed herein. Thus, the inventions
disclosed herein can be embodied or carried out in a manner that
achieves or optimizes one advantage or group of advantages as
taught herein without necessarily achieving other advantages as can
be taught or suggested herein.
BRIEF DESCRIPTION OF THE DRAWINGS
[0008] Throughout the drawings, reference numbers can be re-used to
indicate correspondence between referenced elements. The drawings
are provided to illustrate embodiments of the inventions described
herein and not to limit the scope thereof.
[0009] FIGS. 1A-B are block diagrams illustrating physiological
monitoring systems in accordance with embodiments of the
disclosure;
[0010] FIG. 1C is a top perspective view illustrating portions of a
sensor assembly in accordance with an embodiment of the
disclosure;
[0011] FIG. 2 illustrates a block diagram of an embodiment of a
multiparameter patient monitoring system that includes an acoustic
respiratory monitoring (ARM) sensor and an optical sensor.
[0012] FIG. 3A illustrates an embodiment of an envelope of a
photoplethysmograph waveform.
[0013] FIG. 3B schematically illustrates an example calculation of
pulse wave transit time from two physiological signal inputs.
[0014] FIG. 3C illustrates example power spectrum plots of pulse
wave transit time variability and heart rate variability for
determining respiratory rate measurements.
[0015] FIG. 4 illustrates an embodiment of the multiparameter
patient monitoring system of FIG. 2 coupled to a patient.
[0016] FIG. 5 illustrates a block diagram of an embodiment of a
multiparameter patient monitoring system.
[0017] FIGS. 6A through 6C illustrate block diagrams of embodiments
of respiratory rate measurement calculation systems.
[0018] FIG. 7 illustrates an example multiparameter physiological
monitor.
[0019] FIGS. 8A through 8D illustrate example multiparameter
physiological monitor displays.
[0020] FIG. 9 illustrates an embodiment of a patient monitoring
process in which a user can specify a delay time for an alarm to be
triggered.
[0021] FIG. 10 illustrates an embodiment of a multiparameter
patient monitoring process that allows for dynamic modification of
an alarm delay.
[0022] FIGS. 11 through 17 illustrate embodiments of parameter
confidence displays.
DETAILED DESCRIPTION
[0023] Acoustic sensors, including piezoelectric acoustic sensors,
can be used to measure breath sounds and other biological sounds of
a patient. Breath sounds obtained from an acoustic sensor placed on
the neck, chest, and/or other suitable location can be processed by
a patient monitor to derive one or more physiological parameters of
a patient, including respiratory rate. Respiratory rate can also be
determined from other physiological signals (for example, an ECG
signal, a plethysmographic signal, a bioimpedance signal, and/or
the like) obtained using other sensors and/or instruments.
[0024] Respiratory rate measurements derived from a single sensor
or sensor type can be less accurate at times due to noise, sensor
limitations, body movement, and/or other reasons. Accordingly,
improved multiparameter respiratory rate measurements can be
obtained by jointly processing multiple physiological signals from
multiple sensors and/or sensor types. Alternately, or in addition,
respiratory rate measurements derived from a physiological signal
obtained from one type of sensor can be used to continuously or
periodically refine or assess confidence in the respiratory rate
measurements derived from a physiological signal obtained from
another type of sensor. For example, in certain embodiments,
respiratory rate measurements derived from a plethysmographic
signal obtained by an optical sensor can be used to improve or
determine confidence in the respiratory rate derived from an
acoustic signal obtained by an acoustic sensor.
[0025] This disclosure describes, among other features, systems and
methods for using multiple physiological signals to improve
respiratory or other physiological parameter measurements
reflective of a patient's condition and/or to determine confidence
in these physiological parameter measurements. In certain
embodiments, a patient monitoring system comprises one or more
physiological sensors applied to a living patient and a processor
to monitor the physiological signals received from physiological
sensors. The physiological sensors can include, for example,
acoustic sensors for acquiring breath and/or heart sounds,
electrodes for acquiring ECG and/or bioimpedance signals, and
noninvasive optical sensors to perform pulse oximetry and related
noninvasive analysis of blood constituents.
[0026] In particular, in certain embodiments, a patient monitoring
system can programmatically determine multiparameter confidence in
respiratory rate measurements obtained from an acoustic sensor
based at least partly on inputs obtained from other non-acoustic
sensors or monitors. The patient monitoring system can output a
multiparameter confidence indication reflective of the
programmatically-determined multiparameter confidence. The
multiparameter confidence indication can assist a clinician in
determining whether or how to treat a patient based on the
patient's respiratory rate.
[0027] In certain embodiments, the patient monitoring system can
determine the multiparameter confidence at least in part by
receiving signals from multiple physiological parameter monitoring
devices that are reflective of respiratory rate. For example, a
multiparameter patient monitoring unit can receive a signal
reflective of a respiratory rate from both an acoustic sensor and
an optical sensor. Respiratory rate measurements can be extracted
and/or derived from each of the physiological parameter signals.
The respiratory rate measurement from the acoustic sensor can be
compared with the respiratory rate measurement derived from the
optical sensor signal. Based at least partly on this comparison, a
determination of multiparameter confidence in the
acoustically-derived respiratory rate can be made. A visual or
audible indicator corresponding to this multiparameter confidence
determination, including possibly an alarm, can be output for
presentation to a clinician.
[0028] Additionally, in certain embodiments, the respiratory rate
measurement output to the clinician can be generated based at least
partly on a combination of the multiple respiratory rate
measurements. For example, a respiratory rate measurement derived
from an optical sensor signal can be combined with a respiratory
rate measurement derived from an acoustic sensor signal to produce
an overall respiratory rate. The overall respiratory rate
measurement can be output to the patient monitor display and/or can
be output over a network to another device.
[0029] Moreover, in certain embodiments, the patient monitoring
systems and methods disclosed herein can assess multiparameter
confidence and/or determine respiratory rate based at least partly
on signals received from other physiological parameter monitoring
devices. For example, various measurements obtained from a
capnograph, an electrocardiograph (ECG), a bioimpedance device, or
from other monitoring devices or sensors can be used to assess
multiparameter confidence in acoustic respiratory rate measurements
and/or to determine an overall respiratory rate output.
[0030] For purposes of illustration, this disclosure is described
primarily in the context of respiratory rate. However, the features
described herein can be applied to other respiratory parameters,
including, for example, inspiratory time, expiratory time,
inspiratory to expiratory ratio, inspiratory flow, expiratory flow,
tidal volume, minute volume, apnea duration, breath sounds
(including, e.g., rales, rhonchi, or stridor), changes in breath
sounds, and the like. Moreover, the features described herein can
also be applied to other physiological parameters and/or vital
signs. For example, outputs from multiple monitoring devices or
sensors (e.g., an optical sensor and an ECG monitor) can be used to
assess multiparameter confidence in heart rate measurements, among
other parameters.
[0031] Referring to the drawings, FIGS. 1A through 1C illustrate
example patient monitoring systems, sensors, and cables that can be
used to derive a respiratory rate measurement from a patient. FIGS.
2 through 8 illustrate multiparameter respiratory rate embodiments.
The embodiments of FIGS. 2 through 8 can be implemented at least in
part using the systems and sensors described in FIGS. 1A through
1C.
[0032] Turning to FIG. 1A, an embodiment of a physiological
monitoring system 10 is shown. In the physiological monitoring
system 10, a medical patient 12 is monitored using one or more
sensor assemblies 13, each of which transmits a signal over a cable
15 or other communication link or medium to a physiological monitor
17. The physiological monitor 17 includes a processor 19 and,
optionally, a display 11. The one or more sensors 13 include
sensing elements such as, for example, acoustic piezoelectric
devices, electrical ECG leads, optical sensors, or the like. The
sensors 13 can generate respective signals by measuring a
physiological parameter of the patient 12. The signals are then
processed by one or more processors 19. The one or more processors
19 then communicate the processed signal to the display 11. In an
embodiment, the display 11 is incorporated in the physiological
monitor 17. In another embodiment, the display 11 is separate from
the physiological monitor 17. In one embodiment, the monitoring
system 10 is a portable monitoring system. In another embodiment,
the monitoring system 10 is a pod, without a display, that is
adapted to provide physiological parameter data to a display.
[0033] For clarity, a single block is used to illustrate the one or
more sensors 13 shown in FIG. 1A. It should be understood that the
sensor 13 shown is intended to represent one or more sensors. In an
embodiment, the one or more sensors 13 include a single sensor of
one of the types described below. In another embodiment, the one or
more sensors 13 include one or more acoustic sensors. In still
another embodiment, the one or more sensors 13 include one or more
acoustic sensors and one or more ECG sensors, optical sensors,
bioimpedance sensors, capnography sensors, and the like. In each of
the foregoing embodiments, additional sensors of different types
are also optionally included. Other combinations of numbers and
types of sensors are also suitable for use with the physiological
monitoring system 10.
[0034] In some embodiments of the system shown in FIG. 1A, all of
the hardware used to receive and process signals from the sensors
are housed within the same housing. In other embodiments, some of
the hardware used to receive and process signals is housed within a
separate housing. In addition, the physiological monitor 17 of
certain embodiments includes hardware, software, or both hardware
and software, whether in one housing or multiple housings, used to
receive and process the signals transmitted by the sensors 13.
[0035] As shown in FIG. 1B, the acoustic sensor assembly 13 can
include a cable 25. The cable 25 can include three conductors
within an electrical shielding. One conductor 26 can provide power
to a physiological sensor 13, one conductor 28 can provide a ground
signal from the physiological monitor 17, and one conductor 28 can
transmit signals from the sensor 13 to the physiological monitor
17. For multiple sensors 13, one or possibly more cables 13 can be
provided.
[0036] In some embodiments, the ground signal is an earth ground,
but in other embodiments, the ground signal is a patient ground,
sometimes referred to as a patient reference, a patient reference
signal, a return, or a patient return. In some embodiments, the
cable 25 carries two conductors within an electrical shielding
layer, and the shielding layer acts as the ground conductor.
Electrical interfaces 23 in the cable 25 can enable the cable to
electrically connect to electrical interfaces 21 in a connector 20
of the physiological monitor 17. In another embodiment, the sensor
assembly 13 and the physiological monitor 17 communicate
wirelessly.
[0037] FIG. 1C illustrates an embodiment of a sensor system 100
including a sensor assembly 101 and a monitor cable 111 suitable
for use with any of the physiological monitors shown in FIGS. 1A
and 1B. The sensor assembly 101 includes a sensor 115, a cable
assembly 117, and a connector 105. The sensor 115, in one
embodiment, includes a sensor subassembly 102 and an attachment
subassembly 104. The cable assembly 117 of one embodiment includes
a sensor 107 and a patient anchor 103. A sensor connector
subassembly 105 is connected to the sensor cable 107.
[0038] The sensor connector subassembly 105 can be removably
attached to an instrument cable 111 via an instrument cable
connector 109. The instrument cable 111 can be attached to a cable
hub 120, which includes a port 121 for receiving a connector 112 of
the instrument cable 111 and a second port 123 for receiving
another cable. In certain embodiments, the second port 123 can
receive a cable connected to an optical sensor or other sensor. In
addition, the cable hub 120 could include additional ports in other
embodiments for receiving additional cables. The hub includes a
cable 122 which terminates in a connector 124 adapted to connect to
a physiological monitor (not shown).
[0039] The sensor connector subassembly 105 and connector 109 can
be configured to allow the sensor connector 105 to be
straightforwardly and efficiently joined with and detached from the
connector 109. Embodiments of connectors having connection
mechanisms that can be used for the connectors 105, 109 are
described in U.S. patent application Ser. No. 12/248,856
(hereinafter referred to as "the '856 Application"), filed on Oct.
9, 2008, which is incorporated in its entirety by reference herein.
For example, the sensor connector 105 could include a mating
feature (not shown) which mates with a corresponding feature (not
shown) on the connector 109. The mating feature can include a
protrusion which engages in a snap fit with a recess on the
connector 109. In certain embodiments, the sensor connector 105 can
be detached via one hand operation, for example. Examples of
connection mechanisms can be found specifically in paragraphs
[0042], [0050], [0051], [0061]-[0068] and [0079], and with respect
to FIGS. 8A-F, 13A-E, 19A-F, 23A-D and 24A-C of the '856
Application, for example.
[0040] The sensor connector subassembly 105 and connector 109 can
reduce the amount of unshielded area in and generally provide
enhanced shielding of the electrical connection between the sensor
and monitor in certain embodiments. Examples of such shielding
mechanisms are disclosed in the '856 Application in paragraphs
[0043]-[0053], [0060] and with respect to FIGS. 9A-C, 11A-E, 13A-E,
14A-B, 15A-C, and 16A-E, for example.
[0041] In an embodiment, the acoustic sensor assembly 101 includes
a sensing element, such as, for example, a piezoelectric device or
other acoustic sensing device. The sensing element can generate a
voltage that is responsive to vibrations generated by the patient,
and the sensor can include circuitry to transmit the voltage
generated by the sensing element to a processor for processing. In
an embodiment, the acoustic sensor assembly 101 includes circuitry
for detecting and transmitting information related to biological
sounds to a physiological monitor. These biological sounds can
include heart, breathing, and/or digestive system sounds, in
addition to many other physiological phenomena. The acoustic sensor
115 in certain embodiments is a biological sound sensor, such as
the sensors described herein. In some embodiments, the biological
sound sensor is one of the sensors such as those described in the
'883 Application. In other embodiments, the acoustic sensor 115 is
a biological sound sensor such as those described in U.S. Pat. No.
6,661,161, which is incorporated by reference herein in its
entirety. Other embodiments include other suitable acoustic
sensors.
[0042] The attachment sub-assembly 104 includes first and second
elongate portions 106, 108. The first and second elongate portions
106, 108 can include patient adhesive (e.g., in some embodiments,
tape, glue, a suction device, etc.). The adhesive on the elongate
portions 106, 108 can be used to secure the sensor subassembly 102
to a patient's skin. One or more elongate members 110 included in
the first and/or second elongate portions 106, 108 can beneficially
bias the sensor subassembly 102 in tension against the patient's
skin and reduce stress on the connection between the patient
adhesive and the skin. A removable backing can be provided with the
patient adhesive to protect the adhesive surface prior to affixing
to a patient's skin.
[0043] The sensor cable 107 can be electrically coupled to the
sensor subassembly 102 via a printed circuit board ("PCB") (not
shown) in the sensor subassembly 102. Through this contact,
electrical signals are communicated from the multi-parameter sensor
subassembly to the physiological monitor through the sensor cable
107 and the cable 111.
[0044] In various embodiments, not all of the components
illustrated in FIG. 1C are included in the sensor system 100. For
example, in various embodiments, one or more of the patient anchor
103 and the attachment subassembly 104 are not included. In one
embodiment, for example, a bandage or tape is used instead of the
attachment subassembly 104 to attach the sensor subassembly 102 to
the measurement site. Moreover, such bandages or tapes can be a
variety of different shapes including generally elongate, circular
and oval, for example. In addition, the cable hub 120 need not be
included in certain embodiments. For example, multiple cables from
different sensors could connect to a monitor directly without using
the cable hub 120.
[0045] Additional information relating to acoustic sensors
compatible with embodiments described herein, including other
embodiments of interfaces with the physiological monitor, are
included in U.S. patent application Ser. No. 12/044,883, filed Mar.
7, 2008, entitled "Systems and Methods for Determining a
Physiological Condition Using an Acoustic Monitor," (hereinafter
referred to as "the '883 Application"), the disclosure of which is
hereby incorporated by reference in its entirety. An example of an
acoustic sensor that can be used with the embodiments described
herein is disclosed in U.S. Patent Application No. 61/252,076,
filed Oct. 15, 2009, titled "Acoustic Sensor Assembly," the
disclosure of which is hereby incorporated by reference in its
entirety.
[0046] FIG. 2 illustrates an embodiment of a multiparameter patient
monitoring system 200, which can implement any of the features
described above.
[0047] The multiparameter patient monitoring system 200 includes a
multiparameter patient monitor 205 that receives signals from
multiple physiological parameter measurement devices. The
multiparameter patient monitor 205 can use the multiple received
signals to determine a confidence value for respiratory rate
measurements derived from the signals. The confidence value can
advantageously reflect a degree to which the respiratory rate
measurements derived from the different signals correspond. In
addition, in some embodiments, the multiparameter patient monitor
205 can generate one or more respiratory rate outputs based at
least partly on the multiple received signals.
[0048] The patient monitor 205 can include any of the features of
the physiological monitor 17 described above. The patient monitor
205 can include one or more processors, a display, memory, one or
more input/output (I/O) devices (such as input control buttons,
speakers, etc), a wireless transceiver, a power supply, and/or
processing and filtration circuitry. In certain embodiments, the
patient monitor 205 can communicate with external devices, such as
processing devices, output devices, mass storage devices, and the
like. The patient monitor 205 can communicate with the external
devices via a wired and/or wireless connection. The external
devices can include a central monitoring station (such as a nurses'
monitoring station), a server, a laptop computer, a cell phone, a
smart phone, a personal digital assistant, a kiosk, other patient
monitors, or other clinician devices. The patient monitor 205 can
send physiological data to the external devices.
[0049] In the depicted embodiment, the patient monitor 205 is in
communication with an acoustic sensor 210 and an optical sensor
210. The acoustic sensor 210 can be a piezoelectric sensor or the
like that obtains physiological information reflective of one or
more respiratory parameters of a patient, including respiratory
rate, expiratory flow, tidal volume, minute volume, apnea duration,
breath sounds, riles, rhonchi, stridor, and changes in breath
sounds, such as decreased volume or change in airflow. In addition,
in some cases the acoustic sensor 210 can measure other
physiological sounds, such as heart rate (e.g., to help with
probe-off detection). In certain embodiments, the acoustic sensor
210 can include any of the features described in U.S. Patent
Application No. 61/252,076, filed Oct. 15, 2009, titled "Acoustic
Sensor Assembly," the disclosure of which is hereby incorporated by
reference in its entirety.
[0050] The optical sensor 215 can include a noninvasive optical
sensor that obtains physiological information reflective of one or
more blood parameters of the patient. These parameters can include
one or more of the following: a photoplethysmograph, oxygen
saturation (SpO.sub.2), HbCO, HBMet, FaO.sub.2, fractional oxygen,
total hemoglobin (Hbt), other hemoglobin species, carbon monoxide,
carbon dioxide, pulse rate, perfusion index, pleth variability
index, and optionally others, including concentrations or actual
analyte values of the same. The optical sensor 215 can include one
or more emitters capable of irradiating a tissue site (such as a
finger) with one or more wavelengths of light, such as red and/or
infrared (IR) wavelengths. In one embodiment, the optical sensor
215 is a pulse oximetry sensor. While many optical sensors emit two
wavelengths, certain of the features described herein can be
implemented by a photoplethysmograph sensor that emits a single
wavelength. Further, the optical sensor 215 need not emit red or
infrared wavelengths in certain embodiments but can also emit other
wavelengths. The optical sensor 215 can also include one or more
detectors capable of detecting the light after attenuation by
pulsatile blood and tissue at the measurement site. The one or more
detectors can generate a signal responsive to the attenuated light,
which can be provided to the patient monitor 205.
[0051] The patient monitor 205 can receive signals indicative of
one or more physiological parameters from the acoustic sensor 210
and from the optical sensor 215. The patient monitor 205 can
extract and/or derive respiratory rate measurements from signals
provided by both the acoustic sensor 210 and the optical sensor
215. The patient monitor 205 can also output one or more
respiratory rate measurements for display based at least in part on
the received signals. Example techniques for deriving respiratory
rate from the optical sensor measurements are described below with
respect to FIG. 3.
[0052] In certain embodiments, the patient monitor 205 can use
pulse oximetry respiratory rate measurements to determine a
multiparameter confidence in the acoustic respiratory rate
measurements. The multiparameter confidence can be a value that
reflects a degree of correspondence between the respiratory rate
measurements obtained from the two sensors 210, 215. A close
correspondence (e.g., small difference) between the two respiratory
rate measurements can cause the patient monitor 205 to assign a
higher multiparameter confidence to the acoustic respiratory rate
measurement. Conversely, a larger difference between the two
measurements can result in a lower multiparameter confidence. In
certain embodiments, the patient monitor 205 can instead or also
use the difference in respiratory rate values to assign a
multiparameter confidence to the pulse-oximetry-derived respiratory
rate measurement.
[0053] More generally, any comparative metric can be used to
determine the multiparameter confidence. The comparative metric can
be a difference between the measurements of the two sensors 210,
215 but need not be. Instead, in some embodiments, the comparative
metric can be a ratio between the measurements from the sensors
210, 215, a percentage derived from such a ratio, or the like. Such
a ratio or percentage might be more meaningful than an absolute
difference in some situations. Similarly, the comparative metric
can be a normalization of the measurements from the two sensors
210, 215, such as the following quotient: (the acoustic respiratory
rate--the oximeter respiratory rate)/(the acoustic respiratory
rate) or the like. Other comparative metrics can also be used.
[0054] Additionally, the patient monitor 205 can use pulse oximetry
respiratory rate measurements to refine or adjust the acoustic
respiratory rate measurements in some implementations. For example,
the respiratory rate measurements derived from the two sensors 210,
215 can be combined to form an overall respiratory measurement. The
patient monitor 205 can average the two measurements, for example.
The combined respiratory rate measurement can be more accurate than
a respiratory rate measurement from either sensor 210, 215
alone.
[0055] The patient monitor 205 can output the respiratory rate
measurement derived from either or both of the acoustic and optical
sensors 210, 215. In addition, the patient monitor 205 can output a
multiparameter confidence indicator that reflects the calculated
multiparameter confidence. Examples of multiparameter confidence
indicators are described in greater detail below.
[0056] In certain embodiments, a signal received from the optical
sensor 215 can be analyzed to determine a respiratory rate
measurement. As an illustration of such a signal, FIG. 3A depicts
an example photoplethysmograph (pleth) waveform 300 derived from an
optical sensor. The pleth waveform 300 can be derived from the
received signal by the patient monitor 205. The pleth waveform 300
is plotted on an intensity axis 301 versus a time axis 302. The
pleth waveform 300 has multiple pulses 312, each with a peak 314
and a valley 316 and extending over a time period 318. A curve
extending along the peaks 314 of the pleth waveform 300 represents
an envelope 322 of the pleth waveform 300.
[0057] In certain embodiments, a respiratory rate measurement can
be determined from an analysis of the pleth waveform 300. A
respiratory rate measurement can be determined from the pleth
waveform 300 in the time domain and/or in the frequency domain. In
certain embodiments, a respiratory rate measurement can be
determined from the modulation in the amplitude of the pleth
waveform 300. For example, the time-varying frequency of the
envelope 322 can correspond to the respiratory rate of the patient.
The frequency of the pleth envelope 322 can be determined from the
inverse of the period 324 of the envelope 322. The envelope 322 of
the pleth waveform 300 can be detected by an envelope detector. The
envelope can be identified using an analog envelope detector such
as a diode-based envelope detector or a digital detector employing
such techniques as a Hilbert transform, squaring and low-pass
filtering, or the like.
[0058] The respiratory rate can also be determined from a frequency
analysis of the pleth waveform 300. A frequency spectrum of the
pleth waveform 300 can be generated, for example, by performing a
Fast Fourier Transform (FFT) or other mathematical transform of the
pleth waveform 300. The respiratory rate can be identified by a
peak in the spectrum (e.g., which corresponds to the frequency of
the pleth envelope 322). In certain embodiments, the peak can be
identified by identifying the highest peak in a range of typical
respiratory rates of a human patient. This range can differ for
different patients based on factors such as age, gender,
comorbidity, and the like. A respiratory rate value can be derived
from the frequency of the selected peak. Additional methods of
determining respiratory rate from the pleth waveform 300 and/or an
optical signal are also possible.
[0059] In certain embodiments, instead of or in addition to
analyzing the pleth waveform 300 to obtain respiratory rate, the
patient monitor 205 can obtain respiratory rate from variability
detected in oxygen saturation measurements obtained from the
optical sensor 215. Variations in the oxygen saturation can track
or approximately track the patient's respiratory cycle (e.g., a
cycle of recruitment and collapse of alveoli), as is described in
greater detail in U.S. Application No. 61/222,087, filed Jun. 30,
2009, titled "Pulse Oximetry System for Adjusting Medical
Ventilation," the disclosure of which is hereby incorporated by
reference in its entirety. The magnitude of the time-domain
variations in the oxygen saturation can reflect the degree of
recruitment and collapse of alveoli in the respiratory cycle. In
the frequency domain, a peak in a magnitude response of the
SpO.sub.2 variability within an expected respiratory rate range can
be used to determine a respiratory rate measurement.
[0060] In certain embodiments, the patient monitor 205 can obtain a
respiratory rate measurement from variability detected in a
patient's heart rate. The heart rate can be derived from an ECG
signal, a bioimpedance signal, an acoustic signal, a plethysmograph
signal, and/or combinations of the same.
[0061] In one embodiment, an instantaneous heart rate can be
derived by determining the interval between successive R waves of
the ECG signal and then converting the interval to beats per minute
(bpm). For example, the heart rate can be calculated as 60 divided
by the R-R interval in seconds. In another embodiment, the
instantaneous heart rate can be derived from successive peaks in
the plethysmograph signal. For example, the instantaneous heart
rate can be calculated as 60 divided by the interval in seconds
between the two successive peaks.
[0062] Other techniques can be used to derive the heart rate. For
instance, the heart rate can be determined by analyzing any
successive landmark of an ECG or plethysmograph signal. Further, to
improve noise immunity, the patient monitor 205 can use a more
robust technique to measure the interval, such as autocorrelation
of the ECG or plethysmograph waveform from one beat to the next.
More generally, any technique for reliably measuring the period
from one beat to the next can be used.
[0063] The instantaneous heart rate can be plotted over time to
illustrate variability in the patient's heart rate. In certain
embodiments, the variability in the patient's heart rate is
reflective of the patient's respiratory rate. For example, analysis
of the variability in the instantaneous heart rate in the frequency
domain (for example, by taking the Fourier transform of the
instantaneous heart rate signal in the time domain) can provide an
indication of respiratory rate that can be used to assess
confidence in a respiratory rate measurement derived from an
acoustic sensor or another type of sensor.
[0064] In certain embodiments, the patient monitor 205 can also
obtain a respiratory rate measurement by measuring arterial pulse
wave propagation time from the heart to an extremity. This
propagation time is typically used by blood pressure monitoring
systems and can be estimated by detecting a time difference between
points on an ECG waveform and a photoplethysmograph waveform. This
estimated propagation time is sometimes referred to as pulse wave
transit time (PWTT) or time difference of arrival (TDOA). Currently
available blood pressure monitoring systems trigger an automatic
occlusive cuff to take a blood pressure measurement based on
detected changes in PWTT.
[0065] Variability in the PWTT can be modulated by respiration.
Thus, in certain embodiments, the patient monitor 205 can calculate
PWTT and determine the variability in PWTT measurements over time.
The patient monitor 205 can derive respiratory rate values from the
calculated variability. The patient monitor 205 can use these
values to improve the accuracy of or calculate confidence in
acoustically-derived respiratory values.
[0066] As illustrated in FIG. 3B, in one embodiment, PWTT is
determined as a time difference between a peak of an R-wave 335 of
a QRS complex of an ECG signal 330 to the foot point 345 of a
plethysmograph signal 340. The R-wave 335 represents the first
upward, or positive, deflection of the QRS complex and corresponds
to the time of ventricular depolarization. The foot point 345 of
the plethysmograph signal 340 can correspond to the time of
earliest onset of arrival of the pulse at a location away from the
heart (e.g., at a patient's finger). More generally, PWTT can be
taken as a time interval from any feature of the ECG waveform to
any feature of the pleth waveform. For example, PWTT can be taken
as the interval between the Q or S points of the ECG waveform and a
point such as the midpoint of the pleth waveform.
[0067] The PWTT calculation can be improved by accounting for a
patient's pre-ejection period (PEP). The PEP can include the
difference in time between initiation of ventricular contraction
(e.g., as detected by an ECG) and ejection of blood from the
ventricles into the aorta. The PEP can also be considered as an
interval between the onset of the QRS complex (of an
electrocardiogram) and cardiac ejection. PWTT compensated for PEP
can more accurately represent the propagation time of the arterial
pulse from the heart to an extremity. In order to determine the
PEP, in one embodiment an acoustic sensor is coupled with the
patient to detect a patient's heart sound. The time difference
between a feature of the ECG signal and a feature of the heart
sound (represented as a signal) can be an estimate of PEP. In
another embodiment, a bioimpedance sensor can be used to estimate
PEP by taking a time difference between features of ECG and
bioimpedance sensor signals. The arterial PWTT can then be
calculated by subtracting the PEP from the initial PWTT calculation
obtained from the ECG and plethysmograph signals. The patient
monitor 205 can employ any of the systems or methods for
determining PWTT and PEP described in more detail in U.S.
Provisional Application No. 61/366,862, titled "System for
Triggering A Non-Invasive Blood Pressure Device," filed Jul. 22,
2010, the disclosure of which is hereby incorporated by reference
in its entirety.
[0068] In yet other embodiments, the PWTT is determined from a
landmark of a first plethysmograph signal to a landmark of a second
plethysmograph signal. In some embodiments, the first
plethysmograph signal is acquired from a sensor applied to a finger
of a patient and the second plethysmograph signal is acquired from
a sensor applied to a toe of a patient; however other sensor
locations can be used as desired and/or required.
[0069] The analysis of the heart rate and/or PWTT variability can
include correlation in the time, frequency, or other transform
domains. In one embodiment of a frequency domain analysis, FIG. 3C
illustrates power spectrums 350A, 350B of the PWTT variability and
the heart rate variability of a patient being monitored with the
patient monitor 205. The power spectrums 350A, 350B plot power
amplitude (having an expanded scale) versus frequency. In one
embodiment, the respiratory rate measurement is determined from the
power spectrums 350A, 350B by the highest spectral peak in the
frequency range corresponding to the normal range of respiratory
rates. The respiratory peak 355 of the power spectrums 350A, 350B
is approximately 0.3 Hz, which corresponds to a respiratory rate of
approximately 18 breaths per minute. This is an example frequency
value that can vary for different patients or even for the same
patient over time.
[0070] The respiratory rate measurement derived from the PWTT
variability and the respiratory rate measurement from the heart
rate variability can be compared with each other and/or with other
respiratory rate measurements to determine an overall respiratory
rate measurement or to assess confidence in a respiratory rate
measurement derived from another physiological signal, as described
in further detail below.
[0071] In certain embodiments, the PWTT and/or heart rate
variability data can be smoothed or otherwise filtered by various
signal processing methods, such as moving average smoothing,
sliding average smoothing, box smoothing, binomial (Gaussian)
smoothing, polynomial smoothing, and/or the like, to improve the
accuracy of, or confidence in, the respiratory rate
measurements.
[0072] FIG. 4 illustrates an embodiment of a multiparameter patient
monitoring system 400 coupled to a patient 401. The multiparameter
patient monitoring system 400 includes a patient monitor 405, an
acoustic sensor 410, and an optical sensor 415. The acoustic sensor
410 and the optical sensor 415 can obtain physiological signals
from the patient 401 and transmit the signals to the patient
monitor 405 through cables 403A, 403B.
[0073] As shown, the acoustic sensor 410 is attached to the skin of
the patient 401 on the neck near the trachea. The acoustic sensor
410 can include adhesive elements (e.g., tape, glue, or the like)
to secure the acoustic sensor 410 to the skin. The acoustic sensor
410 can additionally be secured to the patient using an anchor 408,
which can be affixed near a subclavian region of the patient 401 or
at other regions. The anchor 408 can reduce stress on the
connection between the acoustic sensor 410 and the skin during
movement. Other placement locations for the acoustic sensor 410 and
the patient anchor 408 are also possible, such as other parts of
the neck, the chest, or the like.
[0074] The optical sensor 415 can be removably attached to the
finger of the patient 401. In other embodiments, the optical sensor
415 can be attached to a toe, foot, and/or ear of the patient 401.
The optical sensor 415 can include a reusable clip-type sensor, a
disposable adhesive-type sensor, a combination sensor having
reusable and disposable components, or the like. Moreover, the
optical sensor 415 can also include mechanical structures, adhesive
or other tape structures, Velcro.TM. wraps or combination
structures specialized for the type of patient, type of monitoring,
type of monitor, or the like.
[0075] In certain embodiments, the various sensors and/or monitors
can communicate with the patient monitor 405 wirelessly. The
wireless communication can employ any of a variety of wireless
technologies, such as Wi-Fi (802.11x), Bluetooth, cellular
telephony, infrared, RFID, combinations of the same, and the
like.
[0076] In certain embodiments, the multiparameter patient
monitoring system 200 can include additional physiological
parameter measurement devices. FIG. 5 illustrates an example of a
multiparameter respiratory monitoring system 500 that includes
multiple additional measurement devices. In particular, a patient
monitor 505 receives inputs from an acoustic sensor 510, an optical
sensor 515, an electrocardiograph (ECG) 520, a capnograph 525, a
bioimpedance monitor 530, and possibly other physiological monitors
or sensors 535.
[0077] In certain embodiments, the multiparameter patient monitor
505 derives respiratory rate measurements from signals received
from each of the depicted physiological parameter measurement
devices and/or sensors. In certain embodiments, the respiratory
rate measurements derived from one or more of the optical sensor
515, the ECG 520, the capnograph 525, and/or the bioimpedance
monitor 530 can be compared with the respiratory rate measurement
from the acoustic sensor 510. The monitor 505 can compare one or
more of these measurements with the acoustically-derived
measurement in order to derive a multiparameter confidence value
reflecting a confidence in the acoustic respiratory rate
measurement (or confidence in any other of the respiratory rate
measurements).
[0078] In other embodiments, one or more of the respiratory rate
measurements from the ECG 520, the capnograph 525 and the
bioimpedance monitor 530 can be combined with the respiratory rate
measurements from the acoustic sensor 510 and/or the optical sensor
515 to generate a combined respiratory rate output. In certain
embodiments, the combined respiratory rate output can have greater
accuracy than the respiratory rate measurement obtained from any
one of the devices shown.
[0079] The ECG 520 can monitor electrical signals generated by the
cardiac system of a patient. The ECG 520 can include one or more
sensors adapted to be attached to the skin of a patient, which can
be used to detect electrical heart activity of the patient. The ECG
520 can determine any of a variety of electrical physiological
parameters based upon electrical signals received from the one or
more sensors, such as heart rate. In certain embodiments, the ECG
520 can generate an electrocardiogram waveform. The patient monitor
505 can compare one or more features of the waveform with an
acoustically-derived respiratory rate measurement to determine
multiparameter confidence in the acoustically-derived respiratory
rate. For instance, the R-R time period of the ECG waveform, or the
like can be correlated with respiratory rate in certain
individuals. More generally, an envelope of the ECG waveform can
include peaks that the patient monitor 505 can correlate in
frequency with respiratory rate in certain situations.
[0080] The capnograph 525 can determine the carbon dioxide content
in inspired and/or expired air from a patient. For example, the
capnograph 525 can monitor the inhaled and/or exhaled concentration
or partial pressure of carbon dioxide through a breathing mask or
nasal cannula. In certain embodiments, the capnograph 525 can
generate a capnogram responsive to the patient's breathing. The
capnograph 525 can also identify end tidal carbon dioxide
(EtCO.sub.2) levels and/or other values. From the EtCO.sub.2
values, the capnograph 525 can determine a respiratory rate of the
patient. The capnograph 525 can provide this respiratory rate
measurement to the patient monitor 505, which can compare the
respiratory rate with the acoustically-derived respiratory rate to
determine multiparameter confidence.
[0081] The bioimpedance monitor 530 can determine electrical
impedance or resistance in body tissue of a medical patient. For
example, the bioimpedance monitor 530 can include two or more
sensors or electrodes positioned on a patient so as to measure the
bioelectrical impedance or resistance across the chest region. The
measured bioelectrical impedance can vary as a result of the
expansion of the chest due to breathing, and from this variance, a
respiratory rate measurement can be derived. In certain
embodiments, the bioimpedance monitor 530 is a Transthoracic
Impedance Monitor or the like, having two or more electrodes that
can optionally be combined with ECG electrodes. In other
embodiments, the bioimpedance monitor 530 is an impedance
tomograph, having many more electrodes that can also be used to
form a spatial image of the impedance variation.
[0082] The respiratory rate measurement can be derived by the
bioimpedance monitor 530, or alternatively, the bioimpedance
monitor 530 can provide impedance values with respect to time to
the patient monitor 505, which can derive the respiratory rate. The
patient monitor 505 can also compare the impedance-derived
respiratory rate with the acoustically-derived respiratory rate to
determine multiparameter confidence.
[0083] Additional sensors and/or monitors of different types can
also be included. The other patient monitors 135 can include, for
example, thermistor-based breathing sensors or pneumatic breathing
belt sensors.
[0084] In certain embodiments, the electrocardiograph 520, the
capnograph/capnometer 525, and the bioimpedance monitor 530 are
standalone patient monitors that can provide filtered and/or
processed signals to the patient monitor 505. In other embodiments,
the electrocardiograph 520, the capnograph 525, and the
bioimpedance monitor 530 can be replaced with respective sensors,
which each provide physiological data directly to the patient
monitor 505. In still other embodiments, the acoustic sensor 510
and the optical sensor 515 can be replaced with an acoustic
respiratory monitor and a pulse oximeter, respectively. Thus, any
combination of sensors and monitors can provide inputs to the
patient monitor 505, including any subset of the devices shown.
[0085] The patient monitor 505 can output for display the
respiratory rate value derived from the acoustic sensor 550. In
addition, the patient monitor 505 can output respiratory rate
values derived from any of the other devices shown.
[0086] In certain embodiments, the respiratory rate measurements
derived from one or more of the sensors can be used for sequential
hypothesis testing.
[0087] FIGS. 6A through 6C illustrate embodiments of systems 600A,
600B, and 600C for determining multiparameter confidence of
respiratory rate measurements and for outputting respiratory rate
values. The systems 600A, 600B, and 600C can be implemented by any
of the patient monitors described herein, such as the patient
monitors 205, 405, and 505, or by the patient monitors described
below. Each of the depicted blocks of the systems 600A, 600B, and
600C can be implemented by hardware and/or software.
[0088] Referring to FIG. 6A, the system 600A receives signal inputs
reflective of physiological parameters from an acoustic sensor and
from an optical sensor, such as any of the sensors described above.
The signal inputs can be received by respiratory rate determination
blocks 640a, 640b, respectively. Each of the respiratory rate
determination blocks 640 can determine a respiratory rate based at
least in part on its respective signal input. For example, the
respiratory rate determination block 640b can determine respiratory
rate of a patient from a time domain or frequency analysis of a
photopleth input signal.
[0089] In certain embodiments, the respiratory rate determination
block 640b can be part of any of the patient monitors described
above. Thus, for example, an optical sensor could provide the
photopleth signal to the respiratory rate determination block 640b
of a patient monitor, which derives a respiratory rate. The
respiratory rate determination block 640b could instead be part of
a pulse oximetry monitor. The pulse oximetry monitor could
determine a respiratory rate measurement based at least in part on
the photopleth signal. The pulse oximetry monitor could provide the
calculated respiratory rate to the patient monitor (e.g., 205, 405,
505, or the like).
[0090] For convenience, the acoustic respiratory rate measurement
will be described using the shorthand RR.sub.AR and the photopleth
respiratory rate measurement will be described using the shorthand
RR.sub.PO. In the depicted embodiment, the RR.sub.AR and the
RR.sub.PO measurements are provided to a respiratory rate analyzer
645. The respiratory rate analyzer 645 can analyze the RR.sub.AR
and the RR.sub.PO measurements to determine a multiparameter
confidence in the RR.sub.AR measurement. For example, the
respiratory rate analyzer 645 can compare the two measurements to
determine a difference between the two measurements. The
respiratory rate analyzer can derive a multiparameter confidence or
multiparameter confidence value from this calculated difference. In
certain embodiments, the greater the difference between the
RR.sub.AR and the RR.sub.PO measurements, the lower is the
multiparameter confidence determined for the RR.sub.AR measurement.
Conversely, in certain embodiments, the respiratory rate analyzer
645 can use the difference between the two measurements to assign a
multiparameter confidence to the RR.sub.PO measurement.
[0091] The respiratory rate analyzer 645 can output for display a
multiparameter confidence indicator 660 responsive to the
calculated multiparameter confidence along an output respiratory
rate measurement (RR.sub.OUT, described below). The multiparameter
confidence indicator 660 can include a visual and/or audible
indication in various embodiments.
[0092] Moreover, in certain embodiments, the respiratory rate
analyzer 645 can generate the respiratory rate output RR.sub.OUT
based on a combination of the inputs RR.sub.AR and RR.sub.PO. For
example, the respiratory rate analyzer 645 could average the two
respiratory rate inputs. This average could be a weighted average
or the like (see, e.g., FIG. 6C).
[0093] In another embodiment, the respiratory rate analyzer selects
one of the respiratory rate inputs (RR.sub.AR and RR.sub.PO) to
output as the respiratory rate output RR.sub.OUT. The respiratory
rate analyzer 645 could make this selection based at least partly
on single parameter confidence values generated by each respiratory
rate determination block 640a, 640b. These single parameter
confidence values can reflect a quality of the signal received by
each block 640a, 640b. Single parameter confidence values can be
distinguished from multiparameter confidence values, in certain
embodiments, in that single parameter confidence values can reflect
confidence that a respiratory rate derived from a single parameter
is accurate. In contrast, multiparameter confidence values can
reflect respiratory rate accuracy as determined by an analysis of
multiple parameters (e.g., photopleth and ECG).
[0094] For example, the respiratory rate determination block 640b
could determine single parameter confidence of the photopleth
signal using techniques such as those described in U.S. Pat. No.
6,996,427, titled "Pulse Oximetry Data Confidence Indicator," filed
Dec. 18, 2003, (the "'427 patent") the disclosure of which is
hereby incorporated by reference in its entirety. Analogous
techniques could be used by the respiratory rate determination
block 640a to determine single parameter confidence in the quality
of the acoustic respiratory signal received.
[0095] The respiratory rate analyzer 645 could select either the
RR.sub.AR respiratory rate value or the RR.sub.PO respiratory rate
value to provide as the respiratory rate output RR.sub.OUT based
on, for example, which signal has a higher calculated signal
quality. In another embodiment, the respiratory rate analyzer 645
could weight a combination of the two respiratory rate values based
at least in part on the single parameter confidence values. In
various embodiments, the respiratory rate analyzer 645 can also
select the respiratory rate value to output based on
patient-specific factors, such as age, gender, comorbidity, and the
like. For instance, for some patients, one respiratory rate
measurement derived from a particular parameter might be more
reliable than other respiratory rate measurements derived from
other parameters. Many other variations are also possible.
[0096] Although the respiratory rate analyzer 645 has been
described as being able to average respiratory rate values or
select respiratory rate values, the distinction between averaging
and selecting can blur. Selecting, for instance, can be considered
a subset of weighting where respiratory rate values selected are
given a weight of "1" (or substantially 1) and respiratory rate
values not selected are given a weight of "0" (or substantially
0).
[0097] FIG. 6B extends the embodiment shown in FIG. 6A to include
additional parameter inputs. In FIG. 6B, the system 600B receives
an acoustic respiratory signal, a photopleth signal, an ECG signal,
a capnograph signal, and a bioimpedance signal. Signal inputs from
other types of sensors and/or monitors, or additional sensors of
the types listed, can also be received. The respective signal
inputs are received by respiratory rate determination blocks 640a,
640b, 640c, 640d, and 640e. As described above, the respiratory
rate determination blocks 640a, 640b can determine a respiratory
rate measurement using any of the techniques described above and
optionally a single parameter confidence value based at least in
part on its respective signal input. Likewise, the respiratory rate
determination blocks 640c, 640d, and 640e can calculate respiratory
rate measurements and optionally single parameter confidence
values.
[0098] Signal inputs can also be used to determine respiratory rate
measurements derived from heart rate variability and/or PWTT
variability. As shown in FIG. 6B, the signal inputs (e.g., an
acoustic respiratory signal, a photopleth signal, an ECG signal, a
bioimpedance signal and/or other signals) are received by a heart
rate determination block 670 and a PWTT determination block 675. In
other embodiments, more or fewer signal inputs can be received by
the heart rate determination block 670 and/or the PWTT
determination block 675. The heart rate determination block 670 can
derive the patient's heart rate from one or more of the signal
inputs. The PWTT determination block 675 can determine the
patient's PWTT from one or more of the signal inputs using any of
the techniques described above with respect to FIG. 3B.
[0099] The respiratory rate determination blocks 640f and 640g can
determine respiratory rate measurements based at least in part on
an analysis of the heart rate variability and the PWTT variability,
respectively, of the patient, using any of the techniques described
above. For example, the respiratory rate determination blocks 640f
and 640g can determine respiratory rate measurements from a
frequency analysis of heart rate and/or PWTT signals over time. The
respiratory rate measurements calculated by the respiratory rate
determination blocks 640f and 640g can be provided to the
respiratory rate analyzer 650 along with any of the respiratory
rate measurements calculated by the respiratory rate determination
blocks 640a, 640b, 640c, 640d and 640e. The respiratory rate
determination blocks 640f and 640g can also calculate single or
multiple parameter confidence values.
[0100] The respiratory rate determination blocks 640 can be
implemented in any of the patient monitors 205, 405, 505, etc.
described herein. Thus, for example, a patient monitor can receive
sensor inputs from one or more of an acoustic sensor, an optical
sensor, an ECG sensor or sensors, a capnometry sensor, and a
bioimpedance sensor. Not all of the inputs shown need by received
by a patient monitor; rather, a subset can be received by any
patient monitor. From the inputs, the patient monitor implementing
the respiratory rate determination blocks 640 can calculate
individual respiratory rate measurements corresponding to each
input, using any of the techniques described above. The patient
monitor can further implement the respiratory rate determination
blocks 640 by calculating single parameter confidence in each block
in an analogous manner to that described in the '427 patent
incorporated by reference above. In another embodiment, the
respiratory rate calculation for certain of the parameters is
performed in a separate monitor. For instance, a capnograph monitor
can determine a respiratory rate of a patient and provide this
respiratory rate value to a respiratory rate analyzer 650 of the
patient monitor.
[0101] The respiratory rate determination blocks 640 can provide
respiratory rate values and optionally single parameter confidence
values to a respiratory rate analyzer 650. The respiratory rate
analyzer 650 can operate in a similar manner to the respiratory
rate analyzer 645 described above. For instance, the respiratory
rate analyzer 650 can analyze one or more of the respiratory rate
measurements to determine a multiparameter confidence in the
RR.sub.ARM measurement, using any of the techniques described
above.
[0102] In one embodiment, the respiratory rate analyzer 650
determines multiparameter confidence by comparing the RR.sub.AR
measurement to one or more of the other respiratory rate
measurements. The multiparameter confidence calculated by the
respiratory rate analyzer 650 can reflect the differences between
the measurements. For example, the respiratory rate analyzer 650
can average the differences to generate a multiparameter confidence
value, use a weighted average of the differences to generate a
multiparameter confidence value, can select the greatest difference
as the multiparameter confidence value, can use any of the above to
further derive a multiparameter confidence value (e.g., by looking
up the difference value in a look-up table to obtain a
corresponding multiparameter confidence value, or by multiplying
the difference value by a scalar to obtain a multiparameter
confidence value), or by a host of other techniques. Moreover, in
certain embodiments, the respiratory rate analyzer 650 can analyze
any subset of the respiratory rate measurements received to
determine a multiparameter confidence in any given one of the
respiratory rate measurements.
[0103] The respiratory rate analyzer 650 can output for display a
multiparameter confidence indicator 660 responsive to the
calculated multiparameter confidence along an output respiratory
rate measurement (RR.sub.OUT, described below). The multiparameter
confidence indicator 660 can include a visual and/or audible
indication in various embodiments. The multiparameter confidence
indicator 660 can be output to a display 655 along with a
respiratory rate output RR.sub.OUT.
[0104] Moreover, like the respiratory rate analyzer 645 described
above, the respiratory rate analyzer 650 can generate the
respiratory rate output RR.sub.OUT based on a combination or
selection of any of the respiratory rate inputs received from the
various sensors or monitors. For example, the respiratory rate
output RR.sub.OUT can be the acoustic respiratory rate (RR.sub.AR),
or a selected one of the other respiratory rate measurements. Or,
the respiratory rate analyzer 650 could average, perform a weighted
average (e.g., based on respective single parameter confidences),
or otherwise combine the respiratory rate measurements to determine
the respiratory rate output RR.sub.OUT. In various embodiments, the
respiratory rate analyzer 645 can also select and/or combine the
respiratory rate values to determine an output based on
patient-specific factors, such as age, gender, comorbidity, and the
like. For instance, for some patients, one respiratory rate
measurement derived from a particular parameter might be more
reliable than other respiratory rate measurements derived from
other parameters. Many other variations are also possible.
[0105] In other embodiments, the combiner/selector module 650 can
compare the derived respiratory rate measurements to determine,
which, if any, of the respiratory rate determination blocks 640
provided outliers. The combiner/selector module 650 could reject
the outliers and combine (e.g., average) the outputs of the
remaining respiratory rate determination blocks 640.
[0106] In yet other embodiments, the combiner/selector module 650
could determine which of the outputs from the respiratory rate
determination blocks 640 are close to each other (e.g., within a
tolerance) and output a combination of those outputs. For example,
if three of the five respiratory rate determination blocks 640
produce a similar output and two are outliers, the
combiner/selector module 650 could average the three similar
outputs or select one of the three outputs as the final RR.sub.OUT
measurement. Moreover, the combiner/selector module 650 can learn
over time and can select the output derived from one of the sensors
or monitors based on past performance. Many other configurations
and extensions of the combiner/selector module 650 are
possible.
[0107] In certain embodiments, the respiratory rate output
measurements and/or the multiparameter confidence values can be
output to an external device over a network, instead of, or in
addition to, being output to the display 655. For example, the
output data can be output to a central monitoring station (such as
a nurses' monitoring station), a server, a laptop computer, a cell
phone, a smart phone, a personal digital assistant, other patient
monitors, or other clinician devices, for example. In some
embodiments, the patient monitor 505 can transmit data to an
external device via a wireless network using a variety of wireless
technologies, such as Wi-Fi (802.11x), Bluetooth, cellular
telephony, infrared, RFID, combinations of the same, and the
like.
[0108] FIG. 6C illustrates yet another embodiment of a system 600C
for calculating multiparameter confidence in respiratory rate
measurements. In the system 600C, acoustic and photopleth signal
inputs are provided, as well as optionally any number of other
signal inputs (such as any of the inputs described above). As
above, respiratory rate determination blocks 640a, 640b, and so
forth down to 640n can receive these signal inputs. The respiratory
rate determination blocks 640a, 640b, . . . , 640n can calculate
respiratory rate values based on the signal inputs, as well as
associated internal confidence values. Each of the internal
confidence values can reflect an individual respiratory rate block
640 algorithm's confidence in the respiratory rate
measurements.
[0109] A respiratory rate analyzer 660 receives the respiratory
rate and confidence measurements 642 calculated by the respiratory
rate determination blocks 640. The respiratory rate analyzer 660
can have some or all the features of the respiratory rate analyzers
described above. In addition, the respiratory rate analyzer 660 can
use the internal confidence values calculated by the respiratory
rate blocks 640 to weight, select, or otherwise determine
appropriate overall respiratory rate and confidence values 652. The
respiratory rate analyzer 660 outputs these values 652 to a display
655 or to some other device.
[0110] The respiratory rate analyzer 660 can use any of a variety
of techniques to calculate the overall respiratory rate and
confidence 652. Some example techniques are described herein. To
illustrate, in one embodiment, the respiratory rate analyzer 660
can perform a weighted average of the respiratory rate values from
each respiratory rate determination block 640. The weights can be
derived from, or can be, their respective confidence values.
[0111] More complex weighting schemes can also be devised. One
example weighting algorithm can implement an adaptive algorithm for
dynamically adjusting the weights applied to each respiratory rate
value over time. The weights can be adapted based on minimizing
some cost function, such as may be applied by a Kalman filter, for
instance. More generally, any of a variety of adaptive algorithms
may be used to adjust the weights. For example, the respiratory
rate analyzer 660 can implement one or more of the following: a
least mean squares algorithm (LMS), a least squares algorithm, a
recursive least squares (RLS) algorithm, wavelet analysis, a joint
process estimator, an adaptive joint process estimator, a
least-squares lattice joint process estimator, a least-squares
lattice predictor, a correlation canceller, optimized or frequency
domain implementations of any of the above, any other linear
predictor, combinations of the same, and the like.
[0112] In another embodiment, the respiratory rate analyzer 660 can
select the top N available sources having the highest confidence
level, where N is an integer. For instance, the respiratory rate
analyzer 660 can choose the output of N respiratory rate
determination blocks 640 having confidence values that exceed a
threshold. This threshold may be determined relative to the
confidence values provided (e.g., via a ratio or the like) or can
be an absolute threshold. The respiratory rate analyzer 660 can
then perform a weighted average of the remaining values or select
from these values, for example, based on confidence values.
[0113] Internal confidence of each respiratory rate determination
block 640 can depend on a variety of factors, such as signal to
noise ratio, irregularities in the data, probe-off conditions, and
the like. A probe off condition, for instance, can result in a zero
confidence value, a gradual taper down to zero confidence over
time, or the like. Likewise, the confidence values can be derived
from the signal to noise ratio for each respiratory rate
determination block 640.
[0114] FIG. 7 illustrates an example noninvasive multiparameter
physiological monitor 700 that can implement any of the features
described herein. An embodiment of the monitor 700 includes a
display 701 showing data for multiple physiological parameters. For
example, the display 701 can include a CRT or an LCD display
including circuitry similar to that available on physiological
monitors commercially available from Masimo Corporation of Irvine,
Calif. sold under the name Radical.TM., and disclosed in U.S. Pat.
Nos. 7,221,971; 7,215,986; 7,215,984 and 6,850,787, for example,
the disclosures of which are hereby incorporated by reference in
their entirety. However, many other display components can be used
that are capable of displaying respiratory rate and other
physiological parameter data along with the ability to display
graphical data such as plethysmographs, respiratory waveforms,
trend graphs or traces, and the like.
[0115] The depicted embodiment of the display 701 includes a
measured value of respiratory rate 712 (in breaths per minute
(bpm)) and a respiratory rate waveform graph 706. In addition,
other measured blood constituents shown include SpO.sub.2 702, a
pulse rate 704 in beats per minute (BPM), and a perfusion index
708. Many other blood constituents or other physiological
parameters can be measured and displayed by the multiparameter
physiological monitor 700, such as blood pressure, ECG readings,
EtCO.sub.2 values, bioimpedance values, and the like. In some
embodiments, multiple respiratory rates, corresponding to the
multiple input sensors and/or monitors, can be displayed.
[0116] FIGS. 8A through 8C illustrate example multiparameter
physiological monitor displays 801A-801C that output multiparameter
confidence indicators 814. The multiparameter confidence indicators
814 can be generated using any of the techniques described
above.
[0117] Referring to FIG. 8A, an example display 801A is shown that
includes parameter data for respiratory rate, including a measured
respiratory rate value 812 in breaths per minute (bpm) and a
respiratory waveform graph 806. The display 801A also includes
parameter data for SpO.sub.2 802 and pulse rate 804 in beats per
minute (BPM). A respiratory rate multiparameter confidence
indicator 814A is also depicted. In the depicted embodiment, the
multiparameter confidence indicator 814A includes text that
indicates that the current respiratory rate has a low
multiparameter confidence level. The multiparameter confidence
indicator 814A can function as a visual multiparameter
confidence-based alarm by flashing, changing color, or the like
when the multiparameter confidence is below a threshold level. The
multiparameter confidence indicator can include symbols other than
(or in addition to) text in certain embodiments. An audible
multiparameter confidence-based alarm can alternatively, or
additionally, be output through a speaker or other audio output
device. A multiparameter confidence-based alarm can be generated as
described in the '427 patent described above.
[0118] In certain embodiments, an alarm can be output when the
monitored respiratory rate of the patient deviates beyond a
patient-specific and/or patient-independent threshold. The utility
and effectiveness of an alarm based on a respiratory rate
measurement determined solely from an acoustic signal can be
improved by joint processing of ancillary signals from multiple
monitored physiological parameters, such as those described herein
(e.g., electrical signals, photoplethysmographic signals,
bioimpedance signals, and/or the like).
[0119] For example, respiratory rate measurements determined from
the ancillary signals can be used to continuously or periodically
refine or assess confidence in the respiratory rate measurements
derived from the acoustic signal. If the multiparameter confidence
in the acoustic respiratory rate measurement is low, the alarm can
be suppressed, at least pending further consideration; however, if
the multiparameter confidence in the acoustic respiratory rate
measurement is sufficiently high, the alarm can be output without
further consideration.
[0120] In other embodiments, the ancillary signals can be used to
estimate the initial respiratory rate or timing information to
assist an acoustic signal processing algorithm in capturing a
respiratory component of the acoustic signal. The use of the
ancillary signals from multiple parameters to assist in the
capturing of the respiratory component of the acoustic signal can
lead to increased confidence in the accuracy of the respiratory
rate measurement, thereby increasing the accuracy, reliability, and
effectiveness of the alarm based on the respiratory rate
measurement from the acoustic signal.
[0121] The display 801B of FIG. 8B includes the same parameter data
as the display 801A. However, the display 801B includes a
multiparameter confidence indicator 814B that indicates the current
multiparameter confidence level numerically, rather than textually
(displayed as a percentage in the depicted embodiment). A present
multiparameter confidence of 90% is shown by the multiparameter
confidence indicator 814B.
[0122] The display 800C of FIG. 8C includes a respiratory rate
trend graph 816, which depicts respiratory rate measurements over a
period of time. The display 801C also depicts a multiparameter
confidence indicator 814C in the form of a bar graph below the
trend graph 816. The multiparameter confidence indicator 814C
includes bars that can correspond to occurrences of breaths of a
patient. The bars can have a height that corresponds to a degree of
multiparameter confidence in the respiratory rate measurements for
any given breath. As the breaths change over time, the
multiparameter confidence can also change over time, resulting in a
changing multiparameter confidence indicator 814C. The
multiparameter confidence indicator 814C can be generated using
analogous techniques to those described in the '427 patent
described above.
[0123] In certain embodiments, the bars can all be depicted with
the same color and/or pattern or with varying colors and/or
patterns depending on the multiparameter confidence level. For
example, bars within a desired multiparameter confidence range can
be displayed with a first color and/or pattern, bars within a
tolerable multiparameter confidence range can be displayed with a
second color and/or pattern, and bars within a low multiparameter
confidence range can be displayed with a third color and/or
pattern. In certain embodiments, the bars can be replaced with
pulses, lines, or other shapes.
[0124] FIG. 8D illustrates another example multiparameter
physiological monitor 800 having a display 801D. As shown, the
physiological monitor 800 can be configured with a vertical display
instead of a horizontal display. The display 801D can include
similar parameter data as shown in displays 801A-801C. The
multiparameter physiological monitor 800 includes a multiparameter
confidence indicator 814D that is positioned off the display 801D.
The multiparameter confidence indicator 814D can include one or
more light emitting diodes (LEDs) positioned adjacent to text, such
as "LOW RR CONF" or "LOW SO" or "LOW SIQ.TM.," where SQ and SIQ
stand for signal quality and signal intelligence quotient,
respectively. The multiparameter confidence indicator 810D can be
activated to inform a caregiver that a measured value of the
multiparameter confidence of the incoming signal is below a certain
threshold, for instance. In certain embodiments, different colored
LEDs can be used to represent different multiparameter confidence
range levels, such as in the manner described above.
[0125] The example displays 801A-801D in FIGS. 8A-8D are merely
illustrative examples. Many other variations and combinations of
multiparameter confidence indicators 814 are also possible in other
implementations without departing from the spirit and/or scope of
the disclosure.
[0126] Moreover, in certain embodiments, the features described in
U.S. Pat. No. 6,129,675, filed Sep. 11, 1998 and issued Oct. 10,
2000 and in U.S. patent application Ser. No. 11/899,512, filed Sep.
6, 2007, titled "Devices and Methods for Measuring Pulsus
Paradoxus," each of which is hereby incorporated by reference in
its entirety, can be used in combination with the features
described in the embodiments herein.
[0127] FIG. 9 illustrates an embodiment of a patient monitoring
process 900 in which a user (e.g., a clinician) has the ability to
specify a delay time for an alarm to be triggered. In one
implementation, the patient monitoring process 900 is performed by
any of the patient monitoring systems (e.g., systems 10, 200, 400,
500, 600a, 600b) and/or the patient monitors (e.g., monitors 205,
405, 505, 700, 800) described above. More generally, the patient
monitoring process 900 can be implemented by a machine having one
or more processors. Advantageously, in certain embodiments, the
patient monitoring process 900 provides a user-customizable alarm
delay that can reduce nuisance alarms.
[0128] Currently available patient monitoring devices often
generate alarms prematurely or generate alarms that may not
correspond to a clinically significant event. For example, a
monitoring device can generate an alarm even though the patient's
physiological state or condition does not warrant attention.
Instead of providing useful, actionable information, these
"nuisance" alarms can result in unnecessary worry or stress of the
patient and/or clinician and wasted time on the part of the
clinician in responding to the nuisance alarms. The patient
monitoring process 900 can advantageously reduce or suppress the
number of nuisance alarms by providing an alarm delay period. The
alarm delay period can advantageously be adjusted by a user.
[0129] The patient monitoring process 900 begins by receiving user
input of an alarm delay time at block 902. For example, a user such
as a clinician can select a desired alarm delay by inputting the
desired delay time into a physiological monitor via a user
interface, a numerical keypad, or the like. The alarm delay time
can correspond to a particular physiological parameter to be
monitored. The physiological parameter can include, for example,
blood pressure, respiratory rate, oxygen saturation (SpO.sub.2)
level, other blood constitutions and combinations of constitutions,
and pulse, among others. The input from the clinician can adjust a
default alarm delay. For example, the default alarm delay time
might be 15 seconds, and the clinician input can change the alarm
delay time to 30 seconds.
[0130] At block 904, the user-specified alarm delay time is stored
in a memory device. At block 906, the physiological parameter
corresponding to the user-specified alarm delay time is monitored
by a patient monitor of a patient monitoring system. At decision
block 908, t is determined whether a value of the monitored
physiological parameter has remained past a threshold (e.g., above
or below a threshold or thresholds) for the user-specified alarm
delay time. If it is determined that the value of the monitored
physiological parameter has passed a threshold for the time period
of the user-specified alarm delay, an alarm is output at block 910.
If, however, it is determined that the value of the monitored
physiological parameter has not remained past the threshold for the
time period of the user-specified alarm delay, the patient
monitoring process 900 loops back to block 906 to continue
monitoring. In various implementations, the threshold can be set or
adjusted by a user (e.g., a clinician) depending on
patient-specific factors (e.g., age, gender, comorbidity, or the
like).
[0131] The alarm can be provided as a visual and/or audible alarm.
In one embodiment, the alarm is output by a patient monitor. In
another embodiment, the patient monitor transmits the alarm to
another device, such as a computer at a central nurses' station, a
clinician's end user device (e.g., a pod, a pager), or the like,
which can be located in a hospital or at a remote location. The
patient monitor can transmit the alarm over a network, such as a
LAN, a WAN, or the Internet.
[0132] As one example, a user can set an alarm delay time for a
respiratory rate to be sixty seconds. In certain situations, a
respiratory rate that is outside a threshold range of values for
less than sixty seconds can be considered an apnea event.
Accordingly, an alarm generated before the respiratory rate has
remained outside the threshold range of values for a time period of
more than sixty seconds may not be desirable or provide useful
information for a clinician to act on. In one embodiment, the
patient monitor can monitor the respiratory rate by receiving
signals from an acoustic sensor, such as any of the acoustic
sensors described herein. When the patient monitor determines that
the respiratory rate has been outside a threshold range of values
for at least sixty seconds, then an alarm can be output by the
patient monitor.
[0133] In certain embodiments, an indication can be provided to a
user (e.g., a clinician) regarding a current status of the alarm
delay period. The indication can be audible and/or visual. In one
embodiment, a confidence indicator can be altered or modified based
on the alarm delay period. For example, the confidence indicator
can be modified to reflect a "countdown" to the time of triggering
of the alarm. If the confidence indicator is represented by an LED,
for example, the LED can blink once the alarm delay has been
initiated and can blink faster as the trigger time of the alarm
grows closer. If the confidence indicator is represented by a bar
graph, for example, the bars can be modified during the period from
initiation of the alarm delay until the time of triggering of the
alarm. A separate countdown timer that is not coupled with the
confidence indicator could also be provided, which counts down
seconds remaining in the alarm delay period.
[0134] FIG. 10 illustrates an embodiment of a multiparameter
patient monitoring process 1000. In the multiparameter patient
monitoring process 1000, an alarm delay time for a first
physiological parameter can be modified dynamically based on a
measurement of a second physiological parameter. In one
implementation, the patient monitoring process 1000 is performed by
any of the patient monitoring systems (e.g., systems 10, 200, 400,
500, 600a, 600b) and/or the patient monitors (e.g., monitors 205,
405, 505, 700, 800) described above. More generally, the patient
monitoring process 1000 can be implemented by a machine having one
or more processors.
[0135] At block 1006, first and second physiological parameters are
monitored by a multiparameter patient monitor. In one embodiment,
respiratory rate and SpO.sub.2 are the two monitored physiological
parameters. In other embodiments, the first and second monitored
physiological parameters can include, for example, blood pressure,
respiratory rate, oxygen saturation (SpO.sub.2) level, other blood
constitutions and combinations of constitutions, and pulse, among
others.
[0136] At decision block 1008, it is determined whether the current
monitored value of the first physiological parameter has passed a
threshold. If so, then at decision block 1010, it is determined
whether an alarm delay time corresponding to the first parameter
has been reached. The alarm delay time can be a default alarm delay
time or a user-selected delay time, such as the user-selected delay
time described above with respect to FIG. 9. If the first
physiological parameter has not passed the threshold, the
multiparameter patient monitoring process 1000 loops back to block
1006 to continue monitoring.
[0137] If it is determined at decision block 1010 that the
user-specified alarm delay time has been reached, then an alarm is
output at block 1012. If, however, it is determined that the alarm
delay time has not been reached, then the multiparameter patient
monitoring process 1000 proceeds to decision block 1014. The alarm
can have similar features as described above and can be provided
by, on, or to any of the devices described above.
[0138] At decision block 1014, it is determined whether a value of
the second monitored physiological parameter has deviated from a
previous value. If so, then the alarm delay time is dynamically
modified at block 1016, and the process 1000 loops back to block
1006 to continue monitoring. If not, the process 1000 loops back to
decision block 1006 to continue monitoring without changing the
delay time.
[0139] In certain embodiments, a deviation from a previous value
for the second monitored physiological parameter includes a
reduction or increase in value. In other embodiments, a deviation
from a previous value includes a deviation beyond a threshold or
threshold range of acceptable values. The threshold or threshold
range for the second monitored physiological parameter can be set
or adjusted by a user (e.g., a clinician) depending on
patient-specific factors (e.g., age, gender, comorbidity, or the
like). The threshold range of values can be set to include any
range of values.
[0140] In one embodiment, the degree of modification of the alarm
delay can depend on the degree of deviation of the second monitored
physiological parameter. In another embodiment, the degree of
modification of the alarm delay can also depend on the value of the
user-specified or default alarm delay time and/or the identity of
the first physiological parameter being monitored.
[0141] The dynamic modification can be performed in a linear,
step-wise, logarithmic, proportional, or any other fashion. For
example, the change in the alarm delay corresponding to the first
monitored physiological parameter can be proportional to the change
or deviation in the second monitored physiological parameter. In
another embodiment, a series of successive threshold ranges of
values of the second physiological parameter can be provided,
wherein each threshold range corresponds to a different amount of
delay adjustment.
[0142] For example and not by way of limitation, the first
physiological parameter can be respiratory rate and the second
physiological parameter can be SpO.sub.2. In one embodiment, a
user-specified or default alarm delay time can be sixty seconds. If
the respiratory rate is less than a given threshold for less than
the alarm delay time, it can be determined whether the current
SpO.sub.2 level has deviated. Based at least partly on this
deviation, the alarm delay time can be adjusted. For example, if
the SpO.sub.2 level has dropped, the alarm delay time can be
reduced, for example, to 30 seconds, or to 15 seconds, or to
another value. If the second monitored physiological parameter
deviates too far beyond a threshold range, an alarm corresponding
to the second monitored physiological parameter can also be
triggered.
[0143] FIGS. 11 through 17 illustrate additional example
embodiments of physiological parameter displays 1100-1700. These
displays 1100-1700 can be implemented by any physiological monitor,
including any of the monitors described herein. The displays
1100-1700 shown illustrate example techniques for depicting
parameter values and associated confidence. The displays 1100-1700
can be used to depict single parameter (e.g., internal) confidence,
multiparameter confidence, or both. The displays 1100-1700 can be
implemented for respiratory rate or for any other physiological
parameter, including, but not limited to, SpO.sub.2, hemoglobin
species (including total hemoglobin), pulse rate, glucose, or any
of the other parameters described herein.
[0144] Referring initially to FIG. 11, the display 1100 includes an
example parameter value scale 1102 and a plot area 1106. An
indicator 1110 displayed in the plot area 1106 plots a parameter
value 1108 together with associated confidence. In the depicted
embodiment, the indicator 1110 is a normal or Gaussian density
function (e.g., bell curve) that includes a peak 1112. The
indicator 1110 can represent a current (or most recent) parameter
value at the peak 1112 and the confidence associated with that
parameter value.
[0145] The value of the parameter at the peak 1112 matches the
parameter value scale 1102. Thus, for instance, the normal density
function is centered at 8.0, and a superimposed value 1108 of "8.0"
is superimposed on the indicator 1110, indicating a value of 8.0
for the measured parameter. If the parameter is respiratory rate,
the 8.0 can correspond to breaths per minute. If the parameter were
hemoglobin (SpHb), the value can be reported as a concentration in
g/dL (grams per deciliter) or the like. Other parameters, such as
glucose or SpO.sub.2, can have different parameter value scales.
The parameter value scale 1102 and/or the superimposed value 108
are optional and may be omitted in certain embodiments. Likewise,
vertical grid lines 1104 are shown but can be optional, and
horizontal grid lines can also be provided.
[0146] The confidence is represented in certain embodiments by the
characteristics of the indicator 1110 as a normal density function
(or a variation thereof). The normal density function can be
plotted using the Gaussian function or bell curve:
f ( x ) = 1 2 .pi..sigma. 2 e ( x - .mu. ) 2 2 .sigma. 2
##EQU00001##
where parameters .mu. and .sigma..sup.2 are the mean and variance,
respectively. Other related formulas can also be used. In one
embodiment, the indicator 1110 can be plotted by assigning .mu. to
be the parameter value and .sigma..sup.2 (or .sigma., the standard
deviation) to be the computed confidence value (internal,
multiparameter, or a combination of the same). Then, the location
on the parameter scale 1102 of the indicator 1110 can depend on the
value of the parameter (.mu.), and the width or dispersion of the
indicator 1110 can depend on the confidence (.sigma..sup.2 or
.sigma.). Thus, with higher confidence, the variance
(.sigma..sup.2) can be lower, and the curve of the indicator 1110
can be narrower. With lower confidence, the variance can be higher,
and the curve of the indicator 1110 can be wider or more
dispersed.
[0147] The parameter value and/or confidence can have values that
are some linear combination of .mu. and .sigma..sup.2. For
instance, the parameter value can be represented as .alpha..mu.,
where a is a real number. Likewise, the confidence value can be
represented as .beta..sigma..sup.2, where .beta. is a real
number.
[0148] Advantageously, in certain embodiments, the indicator 1110
provides an at-a-glance view of a parameter value and associated
confidence. Because the confidence can be represented as the width
of the indicator 1110, the indicator 1110 can rapidly convey
qualitative as well as quantitative information about confidence to
a clinician. Most clinicians may be familiar with the normal
density function or its associated distribution and may therefore
readily associate the shape of the indicator 1110 with qualitative
meaning regarding confidence.
[0149] Other features of the display 1100 include a phantom
indicator 1120, shown as dashed lines, that represents the
previous-calculated parameter and confidence values. The phantom
indicator 1120 can be used for the immediately previous values, or
multiple phantom indicators 1120 can be used for multiple sets of
previous values. A safety zone bar 1130 is also displayed. The
safety zone bar 1130 includes three areas--a red zone 1132, a
yellow zone 1134, and a green zone 1136, representing unsafe,
marginally safe, and safe parameter values, respectively. If the
peak 1112 of the indicator 1110 is in the green zone 1132, the
value is represented as being safe, and so forth. The colors,
including any colors discussed herein, may be outlines instead of
solid colors. Further, the colors can be replaced with hatch marks,
lines, dots, or any of a variety of other indications to represent
different zones of safety.
[0150] Some example safety zone ranges for respiratory rate for an
adult are as follows. The red, or danger zone 1132 can include
about 5 breaths per minute (BPM) or less. A second red zone (see,
e.g., FIG. 12) might include about 30 BPM or more. The yellow, or
marginally safe zone 1134, can include about 6 BPM to about 10 BPM.
A second yellow zone (see, e.g., FIG. 12) can include about 24 BPM
to about 30 BPM. The green zone 1336 can include about 11 BPM to
about 23 BPM. These ranges are merely examples, however, and can
vary considerably depending on, for instance, patient age, gender,
comorbidity, medications, current activities (e.g., exercising or
sitting), combinations of the same, and the like.
[0151] Although the normal density function has been used to
illustrate confidence, other indicators in other embodiments can be
illustrated using different probability density functions (such as
binomial or Poisson functions). Further, the indicator need not be
illustrated using a probability density function but can instead be
illustrated using one or more boxes, circles, triangles, or other
geometric shapes whose width, length, height, or other property
changes with changing confidence (see, e.g., FIG. 16). Further, the
characteristics of the density function can depend on other factors
in addition to or instead of confidence, such as patient
comorbidities (other diseases can affect the confidence of the
measurement), drugs taken by the patient (which can also affect the
confidence), age, gender, combinations of the same, and the like.
Further, the parameter value scale 1102 can change depending on the
range of the parameter being considered, and a clinician can
optionally zoom in or zoom out to a smaller or larger range.
[0152] Moreover, the safety ranges on the safety zone bar 1130 can
depend on or otherwise be adjusted by a clinician based on patient
comorbidity (e.g., hemoglobinopathy or thalacemia can affect the
safe zones for hemoglobin), medications, age, gender, current
activities or patient condition (such as donating blood, which can
result in a higher start point of the green safety zone for
hemoglobin), combinations of the same, and the like. The
alternative implementations described with respect to FIG. 11, as
well as any of the other features of the display 1100, can be used
for any of the displays 1200-1700 described below as well.
[0153] A variant of the display 1100 is shown as the display 1200
in FIG. 12. The display 1200 also shows an indicator 1210, which
can represent a normal density function as described above with
respect to FIG. 11. As such, the indicator 1210 can represent a
parameter value at a peak of the indicator 1210 and a confidence
value associated with the shape of the indicator. In this indicator
1210, however, the indicator 1210 itself is colored to show
vertical safety zones 1240, 1242, and 1244. These safety zones can
be similar to the safety zones described above with respect to the
safety zone bar 1130 of FIG. 11.
[0154] The safety zone 1240 can represent a green or safe zone, the
safety zone 1242 can represent a yellow or marginal zone, and the
zone 1244 can represent a red or danger zone. Although the
indicator 1210 is centered on these zones, different values of the
parameter represented by the indicator 1210 can shift the indicator
1210 closer toward one or more of the zones. Thus, the color of the
indicator 1210 can change, for example, be entirely yellow, or
entirely red, or entirely green, or some different combination of
the same. Further, the display 1200 can be modified in some
embodiments to add a safety zone bar like the safety zone bar 1130
of FIG. 11. The colors of the safety zone bar can vertically match
the colors above the bar shown in the indicator 1210 (see, e.g.,
FIG. 14).
[0155] FIG. 13 depicts another embodiment of a display 1300.
Similar to the displays 1100, 1200, the display 1300 includes an
indicator 1310 that uses normal density function features to
represent a parameter value and confidence. However, the indicator
1310 includes horizontal safety zones 1340, 1342, 1344. The
horizontal zones can be similar to the safety zones described above
and can include, for example, red, green, and yellow (or other)
colors. In another embodiment (not shown), the indicator 1310 can
be a single solid color corresponding to the safety zone of the
peak of the indicator 1310. The indicator 1310 can also include
gradual instead of abrupt transitions between colors.
[0156] Referring to FIG. 14, a display 1400 includes an indicator
1410 having the density function characteristics described above.
In addition, the indicator 1410 is colored vertically with safety
zones 1442 and 1444, similar to the indicator 1210 above. In
addition, a safety zone bar 1430 is also shown, which has colors
that correspond vertically to the colors of the indicator 1410.
Thus, a zone 1440 can be green, the zones 1442 and 1452 (of the bar
1430) can be yellow, and the zones 1444 and 1454 (of the bar) can
be red, or the like.
[0157] FIG. 15 illustrates a display 1500 having an indicator 1510
without color. Instead, the indicator 1510, which can include the
features of the indicators described above, includes markings 1520
to reflect percentages of standard deviations of the normal density
function. These standard deviations can correspond to confidence
intervals. These markings 1520 include horizontal arrows, vertical
lines, and associated percentage numbers to mark a first standard
deviation (e.g., 68% confidence that the parameter lies within the
interval marked by the arrow), a second standard deviation (e.g.,
95% confidence that the parameter lies within the interval marked
by the arrow), and the third standard deviation (e.g., 99%
confidence interval). Color or safety zones can be added to the
indicator 1510 as in any of the other example indicators described
herein.
[0158] FIG. 16 illustrates yet another display 1600 with an
indicator 1600. Unlike the indicators described above, the
indicator 1610 is not a bell curve but instead a geometric
arrangement of vertical bars 1612. The vertical bars 1612 can
approximate a bell curve, however. Horizontal bars may also be used
similarly. The width of the vertical bars 1612 and/or the width of
the indicator 1600 as a whole can represent the confidence of a
parameter. Further, the parameter value can be represented by the
center bar 1612 on a parameter value scale (not shown; see FIG.
11). The narrower the indicator 1610, the more confidence is
represented, and the wider the indicator 1610, the less confidence
is represented, in one embodiment.
[0159] Referring to FIG. 17, another embodiment of a display 1700
is shown. The display 1700 illustrates additional features that can
be combined with any of the embodiments described above. The
display 1700 includes two indicators 1710a, 1710b. Each of the
indicators 1710 is asymmetrical instead of bell-curve shaped. On
one side of the peak 1712a, 1712b for each indicator 1710a, 1710b,
a portion 1714a, 1714b of the curve is wider or more dispersed than
the other side, leading to the asymmetry.
[0160] In one embodiment, the indicator 1710 can be asymmetrical if
the confidence measure indicates higher confidence on one side of
the parameter value as opposed to the other. Asymmetric confidence
can occur for some parameters due to bias. For instance, with
hemoglobin, a bias for more positive values at lower values of
hemoglobin may occur based on the levels of other blood
constituents such as oxygen saturation (SpO.sub.2) or
carboxyhemoglobin (SpCO). Similarly, hemoglobin can have a bias for
more negative values at higher values of hemoglobin based on levels
of other blood constituents. Thus, for lower values of hemoglobin,
the curve may be wider in the positive direction, and vice
versa.
[0161] Positive asymmetry for lower parameter values is illustrated
by the indicator 1710a, while negative asymmetry for higher
parameter values is illustrated by the indicator 1710b. To
illustrate both positive and negative asymmetry, two indicators
1710a, 1710b are depicted on the display 1700. However, in one
implementation, only one indicator 1710 is displayed. Multiple
indicators are also possible, such as for multiple parameters on a
single display. Moreover, the features described herein with
respect to FIG. 17 can be extended to arbitrary geometric shapes. A
triangle, for instance, can have one half that is wider than
another half based on positive or negative bias in confidence
levels.
[0162] Any of the displays 1100-1700 can be used to indicate the
occurrence and/or severity of an alarm. For instance, the
indicators described above can pulsate or flash when an alarm
occurs, optionally in conjunction with an audible alarm. The
seriousness of the alarm can depend at least partially on the
measured confidence. Higher confidence (e.g., a narrow indicator)
can result in a more urgent alarm, whereas less urgent alarms can
result for less confident parameter values. This urgency can be
displayed in a variety of ways, for example, by increasing the rate
that the indicator flashes, increasing the frequency and/or pitch
of an audible alarm, combinations of the same, and the like.
[0163] Conditional language used herein, such as, among others,
"can," "could," "might," "may," "e.g.," and the like, unless
specifically stated otherwise, or otherwise understood within the
context as used, is generally intended to convey that certain
embodiments include, while other embodiments do not include,
certain features, elements and/or states. Thus, such conditional
language is not generally intended to imply that features, elements
and/or states are in any way required for one or more embodiments
or that one or more embodiments necessarily include logic for
deciding, with or without author input or prompting, whether these
features, elements and/or states are included or are to be
performed in any particular embodiment.
[0164] Depending on the embodiment, certain acts, events, or
functions of any of the methods described herein can be performed
in a different sequence, can be added, merged, or left out all
together (e.g., not all described acts or events are necessary for
the practice of the method). Moreover, in certain embodiments, acts
or events can be performed concurrently, e.g., through
multi-threaded processing, interrupt processing, or multiple
processors or processor cores, rather than sequentially.
[0165] The various illustrative logical blocks, modules, circuits,
and algorithm steps described in connection with the embodiments
disclosed herein can be implemented as electronic hardware,
computer software, or combinations of both. To clearly illustrate
this interchangeability of hardware and software, various
illustrative components, blocks, modules, circuits, and steps have
been described above generally in terms of their functionality.
Whether such functionality is implemented as hardware or software
depends upon the particular application and design constraints
imposed on the overall system. The described functionality can be
implemented in varying ways for each particular application, but
such implementation decisions should not be interpreted as causing
a departure from the scope of the disclosure.
[0166] The various illustrative logical blocks, modules, and
circuits described in connection with the embodiments disclosed
herein can be implemented or performed with a general purpose
processor, a digital signal processor (DSP), an application
specific integrated circuit (ASIC), a field programmable gate array
(FPGA) or other programmable logic device, discrete gate or
transistor logic, discrete hardware components, or any combination
thereof designed to perform the functions described herein. A
general purpose processor can be a microprocessor, but in the
alternative, the processor can be any conventional processor,
controller, microcontroller, or state machine. A processor can also
be implemented as a combination of computing devices, e.g., a
combination of a DSP and a microprocessor, a plurality of
microprocessors, one or more microprocessors in conjunction with a
DSP core, or any other such configuration.
[0167] The blocks of the methods and algorithms described in
connection with the embodiments disclosed herein can be embodied
directly in hardware, in a software module executed by a processor,
or in a combination of the two. A software module can reside in RAM
memory, flash memory, ROM memory, EPROM memory, EEPROM memory,
registers, a hard disk, a removable disk, a CD-ROM, or any other
form of computer-readable storage medium known in the art. An
exemplary storage medium is coupled to a processor such that the
processor can read information from, and write information to, the
storage medium. In the alternative, the storage medium can be
integral to the processor. The processor and the storage medium can
reside in an ASIC. The ASIC can reside in a user terminal. In the
alternative, the processor and the storage medium can reside as
discrete components in a user terminal.
[0168] While the above detailed description has shown, described,
and pointed out novel features as applied to various embodiments,
it will be understood that various omissions, substitutions, and
changes in the form and details of the devices or algorithms
illustrated can be made without departing from the spirit of the
disclosure. As will be recognized, certain embodiments of the
inventions described herein can be embodied within a form that does
not provide all of the features and benefits set forth herein, as
some features can be used or practiced separately from others. The
scope of certain inventions disclosed herein is indicated by the
appended claims rather than by the foregoing description. All
changes which come within the meaning and range of equivalency of
the claims are to be embraced within their scope.
* * * * *